Naturopathy Special Interest Group Research Capacity and Needs Assessment Survey
Bibliographic record
Abstract
OBJECTIVES: Despite recent shifts in regulation and recognition of the role that naturopathy plays in health care delivery in Canada, comparatively little research has been conducted regarding individuals who conduct naturopathy-related research. A survey was undertaken to better understand the needs and capacity of these individuals to conduct more research. DESIGN, SETTING, AND SUBJECTS: The Naturopathy Special Interest Group (N-SIG) of the Interdisciplinary Network of Complementary and Alternative Medicine (INCAM) Researchers created and distributed a survey of individuals interested in naturopathy-related research to assess gaps between current and desired research activity and needs for further participation. OUTCOME MEASURES: Results from a previous pilot study (2014; n = 58) were used to inform the design and distribution. This study received approval and oversight from the Research Ethics Board of the Canadian College of Naturopathic Medicine. RESULTS: The survey was completed by 201 individuals (∼5%-10% of all naturopathic doctors and naturopathy researchers in Canada). The majority (70%) had no peer-reviewed publication experience; however, 63% reported having published in a nonpeer-reviewed medium. Respondents reported differing levels of confidence in completing various components of a research project. Frequently selected obstacles included lack of time due to professional and personal obligations, as well as insufficient training, funding, and mentorship. The greatest identified needs for participation in research were mentorship/support, access to a wider degree of scientific journals, and targeted funding opportunities for CAM research. Overall, the results of this survey suggest that there is interest in further conducting naturopathy-related research in Canada. There are individuals who are already involved and have expressed skills in the area of evidence-based medicine. Mentorship, research training, resources, and critical appraisal and writing skills may be important leverage points. CONCLUSION: Findings from this investigation will be used to inform an agenda for naturopathy-related research and activities of the N-SIG with respect to enhancing research capacity. Other CAM groups or geographic regions could consider using similar methodology to assess capacity and needs for research participation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".